Association of Heart Rate at Hospital Discharge With Mortality and Hospitalizations in Patients With Heart Failure
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is associated with a high burden of morbidity and mortality. Hospital discharge is an opportunity for identification of modifiable prognostic factors in the transition to chronic HF. METHODS AND RESULTS: We examined the association of discharge heart rate with 30-day and 1-year mortality and hospitalization outcomes in a cohort of 9097 patients with HF discharged from hospital. Discharge heart rate was categorized into predefined groups: 40 to 60 (n=1333), 61 to 70 (n=2170), 71 to 80 (n=2631), 81 to 90 (n=1700), and >90 bpm (n=1263). There was a significant increase in all-cause 30-day mortality with adjusted odds ratios of 1.59 (95% confidence interval [CI], 1.18-2.14; P=0.003) for discharge heart rates 81 to 90 bpm and 1.56 (95% CI, 1.13-2.16; P=0.007) for heart rates>90 bpm when compared with the reference group (heart rates, 61-70 bpm). Cardiovascular death risk at 30 days was also higher with adjusted odds ratio 1.59 (discharge heart rates, 81-90 bpm; 95% CI, 1.09-2.33; P=0.017) and 1.65 (discharge heart rates, >90 bpm; 95% CI, 1.09-2.48; P=0.017). One-year all-cause mortality (adjusted odds ratio, 1.41; 95% CI, 1.16-1.72; P<0.001) and cardiovascular death (adjusted odds ratio, 1.47; 95% CI, 1.12-1.92; P=0.005) were higher with discharge heart rates>90 bpm when compared with the reference group (heart rates, 40-60 bpm). Readmissions for HF (adjusted hazard ratio, 1.26; 95% CI, 1.04-1.54; P=0.021) and cardiovascular disease (adjusted hazard ratio, 1.29; 95% CI, 1.08-1.54; P=0.004) within 30 days were also higher with discharge heart rates>90 bpm. CONCLUSIONS: Higher discharge heart rates were associated with greater risk of all-cause and cardiovascular mortality≤1-year follow-up and an elevated risk of 30-day readmission for HF and cardiovascular disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".